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Unity Pyramids

Developed by ra-XOr
This is a PPO agent model trained with Unity ML-Agents, specifically designed for the pyramid game environment
Object Detection
TensorBoard
#Unity Game AI#Deep Reinforcement Learning#PPO Algorithm
Downloads 23
Release Time : 6/27/2022

Model Overview

An agent trained using deep reinforcement learning (PPO algorithm) that can autonomously navigate and complete tasks in Unity's 3D pyramid game environment

Model Features

Built on Unity ML-Agents Framework
Trained using Unity's official machine learning agents framework, seamlessly integrated with the Unity game engine
PPO Algorithm Implementation
Utilizes Proximal Policy Optimization (PPO), an advanced reinforcement learning algorithm for training
3D Environment Interaction
Capable of navigation and decision-making in complex 3D pyramid game environments

Model Capabilities

3D Environment Navigation
Obstacle Avoidance
Goal-oriented Behavior
Reinforcement Learning Decision-making

Use Cases

Game AI
Pyramid Game AI
Functions as an autonomous agent in pyramid games, capable of completing game objectives
Actual performance can be viewed on Hugging Face Spaces
Reinforcement Learning Research
3D Navigation Research
Can serve as a benchmark model for studying agent navigation behavior in 3D environments
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